pythia160m-rm-tldr6.9b

This model is a fine-tuned version of mnoukhov/pythia160m-sft-tldr on an unknown dataset. It achieves the following results on the evaluation set:

• Loss: 0.5399
• Accuracy: 0.7213

Model description

More information needed

Intended uses & limitations

More information needed

Training and evaluation data

More information needed

Training procedure

Training hyperparameters

The following hyperparameters were used during training:

• learning_rate: 1e-05
• train_batch_size: 8
• eval_batch_size: 8
• seed: 42
• distributed_type: multi-GPU
• num_devices: 4
• gradient_accumulation_steps: 2
• total_train_batch_size: 64
• total_eval_batch_size: 32
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: cosine
• num_epochs: 1

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
0.596	0.2006	291	0.5819	0.6923
0.5382	0.4011	582	0.5513	0.7151
0.505	0.6017	873	0.5480	0.7141
0.4836	0.8022	1164	0.5399	0.7213

Framework versions

• Transformers 4.41.1
• Pytorch 2.2.1+cu121
• Datasets 2.19.0
• Tokenizers 0.19.1